Optimizers are algorithms responsible for reducing the loss function in order to find its global minima and, hence, finding the most accurate results. They update the neural network weights and learning rate to achieve this goal. In our analysis, we have evaluated two optimizers: Stochastic Gradient Descent (SGD) and Adaptive Moment Estimation (ADAM) [1]}.
